Statistics – Applications
Scientific paper
Jun 1997
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1997spie.3086..184g&link_type=abstract
Proc. SPIE Vol. 3086, p. 184-192, Acquisition, Tracking, and Pointing XI, Michael K. Masten; Larry A. Stockum; Eds.
Statistics
Applications
Scientific paper
There are numerous types of real-time processing applications with diverse requirements. Even though application requirements vary significantly, they share many common elements. An integrated image processing software architecture applicable to multiple image processing applications is beneficial in reducing software costs, increasing information fusion, and rapidly prototyping demonstration systems. This paper describes an image processing architecture that provides a framework for integrating multiple image processing applications such as image-based target trackers, IR search and track (IRST), and automatic target cueing/recognition. It discusses the general image processing structure describing common and unique elements of these different applications including such issues as throughput, control and data flow, and latency requirements. We describe the integrated architecture including data input, processing parallelization, image and data processing, information fusing, interfaces, and displays. We present examples of image-based target tracking, moving target indication and IRST implemented using this software architecture on parallel processors. The integrated image processing framework has proven to be extremely beneficial for rapid development of image processing systems form the concept to the demonstration stage.
Chidambara Madhu
Cody Robert F.
Groves Gillian K.
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